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Title:	A global monthly climatology of total alkalinity: a neural network approach (Discussions version) [Dataset]
Authors:	Broullón, Daniel; Pérez, Fiz F. ; Velo, A. ; Hoppema, M.; Olsen, Are; Takahashi, Taro; Key, Robert M.; González-Dávila, Melchor; Tanhua, T.; Jeansson, Emil; Kozyr, Alex; Van Heuven, S.
Keywords:	Total alkalinity Monthly climatology Neural network Ocean acidification
Issue Date:	2018
Citation:	Broullón, Daniel; Pérez, Fiz F.; Velo, A.; Hoppema, M.; Olsen, Are; Takahashi, Taro; Key, Robert M.; González-Dávila, Melchor; Tanhua, T.; Jeansson, Emil; Kozyr, Alex; Van Heuven, S.; 2018; “A global monthly climatology of total alkalinity: a neural network approach (Discussions version) [Dataset]”; Digital.CSIC; http://dx.doi.org/10.20350/digitalCSIC/8564
Description:	The item is made of 6 files: 1) Readme_Global_monthly_dataset.txt; 2) ATNNWOA13.nc is the climatological data of total alkalinity computed with NNGv2; 3) NNGv2 is the neural network object used to create the climatology; 4) NNw3RMSE is a neural network object used to evaluate the error of the network when it is trained without data beyond +-3RMSE; 5)ATNNWOA13.mp4 is a video of the surface climatology, 3 vertical sections in the Pacific Ocean, Atlantic Ocean and Indean Ocean and, the variation in depth of one month (April); 6) Example.rar contains an example matrix of inputs to the neural network, the NNGv2.mat and a MATLAB script to compute AT with NNGv2.-- The final version is in http://dx.doi.org/10.20350/digitalCSIC/8644
URI:	http://hdl.handle.net/10261/169529
DOI:	http://dx.doi.org/10.20350/digitalCSIC/8564
Appears in Collections:	(IIM) Conjuntos de datos